Demo Quarto + R + Github

Cette page web est générée automatiquement à partir d’un unique fichier quarto (.qmd).

Explications

Quarto est le “successeur” de RMarkdown. Il offre un éventail de possibilité immense pour créer des rapports, sites webs, livres, etc.

Les examples suivants utilisent principalement ggplot2 et ggiraph. Ils sont tirés de cette page: r-graph-gallery.com/package/ggiraph.html

Préparation

library(ggiraph)
library(tidyverse)
library(patchwork)
library(ggthemes)
library(sf)

Example simple

mtcars_db <- rownames_to_column(mtcars, var = "carname")

scatter <- ggplot(
  data = mtcars_db,
  mapping = aes(
    x = disp, y = qsec,
    tooltip = carname, data_id = carname
  )
) +
  geom_point_interactive(
    size = 3, hover_nearest = TRUE
  ) +
  labs(
    title = "Displacement vs Quarter Mile",
    x = "Displacement", y = "Quarter Mile"
  ) +
  theme_bw()

bar <- ggplot(
  data = mtcars_db,
  mapping = aes(
    x = reorder(carname, mpg), y = mpg,
    tooltip = paste("Car:", carname, "<br>MPG:", mpg),
    data_id = carname
  )
) +
  geom_col_interactive(fill = "skyblue") +
  coord_flip() +
  labs(
    title = "Miles per Gallon by Car",
    x = "Car", y = "Miles per Gallon"
  ) +
  theme_bw()

combined_plot <- scatter + bar +
  plot_layout(ncol = 2)

interactive_plot <- girafe(ggobj = combined_plot) |>
   girafe_options(
      opts_hover(css = "fill:cyan;stroke:black;cursor:pointer;"),
      opts_selection(type = "single", css = "fill:red;stroke:black;")
   )

interactive_plot

Carte interactive

atlas <- readr::read_rds(
  "https://github.com/viniciusoike/restateinsight/raw/main/static/data/atlas_sp_hdi.rds"
)

pop_hdi <- atlas |>
  st_drop_geometry() |>
  mutate(
    group_hdi = findInterval(HDI, seq(0.65, 0.95, 0.05), left.open = FALSE),
    group_hdi = factor(group_hdi)
  ) |>
  group_by(group_hdi) |>
  summarise(score = sum(pop, na.rm = TRUE)) |>
  ungroup() |>
  mutate(share = score / sum(score) * 100) |>
  na.omit() |>
  mutate(
    y_text = if_else(group_hdi %in% c(0, 7), share + 3, share - 3),
    label = paste0(round(share, 1), "%"),
    data_id = as.character(group_hdi) # Add data_id to pop_hdi
  )

atlas <- atlas |>
  mutate(group_hdi = findInterval(HDI, seq(0.65, 0.95, 0.05), left.open = FALSE))

pmap <- ggplot(atlas) +
  geom_sf_interactive(aes(fill = HDI, data_id = group_hdi, tooltip = paste("HDI:", HDI)), lwd = 0.05, color = "white") +
  scale_fill_fermenter(
    name = "",
    breaks = seq(0.65, 0.95, 0.05),
    direction = 1,
    palette = "YlGnBu"
  ) +
  labs(
    title = "HDI in Sao Paulo, BR (2010)",
    subtitle = "Microregion HDI in Sao Paulo",
    caption = "Source: Atlas Brasil"
  ) +
  theme_map() +
  theme(
    legend.position = "none",
    plot.title = element_text(size = 16, hjust = 0.5),
    plot.subtitle = element_text(hjust = 0.5)
  )

x_labels <- c(
  "0.650 or less", "0.650 to 0.699", "0.700 to 0.749", "0.750 to 0.799",
  "0.800 to 0.849", "0.850 to 0.899", "0.900 to 0.949", "0.950 or more"
)

pcol <- ggplot(pop_hdi, aes(group_hdi, share, fill = group_hdi)) +
  geom_col_interactive(aes(data_id = data_id, tooltip = paste("Share:", label))) +
  geom_hline(yintercept = 0) +
  geom_text_interactive(
    aes(y = y_text, label = label, color = group_hdi, data_id = data_id),
    size = 2
  ) +
  coord_flip() +
  scale_x_discrete(labels = x_labels) +
  scale_fill_brewer(palette = "YlGnBu") +
  scale_color_manual(values = c(rep("black", 5), rep("white", 2), "black")) +
  guides(fill = "none", color = "none") +
  labs(
    title = "",
    x = NULL,
    y = NULL
  ) +
  theme_void() +
  theme(
    panel.grid = element_blank(),
    plot.title = element_text(size = 8), # Reduced title size
    axis.text.y = element_text(size = 5), # Reduced y-axis text size
    axis.text.x = element_blank(),
    aspect.ratio = 1.5
  )

p_hdi_atlas <- pmap + pcol + plot_layout(widths = c(3, 1))
p_hdi_atlas <- pmap + inset_element(pcol, left = 0.5, bottom = 0, right = 1, top = 0.5)

interactive_plot <- girafe(
  ggobj = p_hdi_atlas,
  options = list(
    opts_hover(css = "fill:orange;"),
    opts_hover_inv(css = "opacity:0.5;"),
    opts_selection(type = "single", only_shiny = FALSE)
  )
)

interactive_plot

Interaction + CSS

world_sf <- read_sf("https://raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/world.geojson")
world_sf <- world_sf %>%
  filter(!name %in% c("Antarctica", "Greenland"))

happiness_data <- data.frame(
  Country = c(
    "France", "Germany", "United Kingdom",
    "Japan", "China", "Vietnam",
    "United States of America", "Canada", "Mexico"
  ),
  Continent = c(
    "Europe", "Europe", "Europe",
    "Asia", "Asia", "Asia",
    "North America", "North America", "North America"
  ),
  Happiness_Score = rnorm(mean = 30, sd = 20, n = 9),
  GDP_per_capita = rnorm(mean = 30, sd = 20, n = 9),
  Social_support = rnorm(mean = 30, sd = 20, n = 9),
  Healthy_life_expectancy = rnorm(mean = 30, sd = 20, n = 9)
)

world_sf <- world_sf %>%
  left_join(happiness_data, by = c("name" = "Country"))

p1 <- ggplot(world_sf, aes(
  GDP_per_capita,
  Happiness_Score,
  tooltip = name,
  data_id = name,
  color = name
)) +
  geom_point_interactive(data = filter(world_sf, !is.na(Happiness_Score)), size = 4) +
  theme_minimal() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none"
  )

p2 <- ggplot(world_sf, aes(
  x = reorder(name, Happiness_Score),
  y = Happiness_Score,
  tooltip = name,
  data_id = name,
  fill = name
)) +
  geom_col_interactive(data = filter(world_sf, !is.na(Happiness_Score))) +
  coord_flip() +
  theme_minimal() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none"
  )

p3 <- ggplot() +
  geom_sf(data = world_sf, fill = "lightgrey", color = "lightgrey") +
  geom_sf_interactive(
    data = filter(world_sf, !is.na(Happiness_Score)),
    aes(fill = name, tooltip = name, data_id = name)
  ) +
  coord_sf(crs = st_crs(3857)) +
  theme_void() +
  theme(
    axis.title.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "none"
  )

combined_plot <- (p1 + p2) / p3 + plot_layout(heights = c(1, 2))

Sans CSS

interactive_plot <- girafe(ggobj = combined_plot)
interactive_plot

Avec CSS

tooltip_css <- "
  border-radius: 12px;
  color: #333;
     background-color: white;
   padding: 10px;
  font-size: 14px;
  transition: all 0.5s ease-out;
"

hover_css <- "
  filter: brightness(75%);
  cursor: pointer;
  transition: all 0.5s ease-out;
  filter: brightness(1.15);
"

interactive_plot <- girafe(ggobj = combined_plot)
interactive_plot <- interactive_plot |>
  girafe_options(
    opts_hover(css = hover_css),
    opts_tooltip(css = tooltip_css),
    opts_hover_inv(css = "opacity:0.3; transition: all 0.2s ease-out;")
  )
interactive_plot